django-silk VS Ray

But that's still not backend-specific SQL?

There should be an interface method for this. Why does psycopg call it mogrify?

https://django-debug-toolbar.readthedocs.io/en/latest/panels... :

> debug_toolbar.panels.sql.SQLPanel: SQL queries including time to execute and links to EXPLAIN each query

But debug toolbars mostly don't work with APIs.

https://github.com/django-query-profiler/django-query-profil... :

> Django query profiler - one profiler to rule them all. Shows queries, detects N+1 and gives recommendations on how to resolve them

https://github.com/jazzband/django-silk :

> Silk is a live profiling and inspection tool for the Django framework. Silk intercepts and stores HTTP requests and database queries before presenting them in a user interface for further inspection

you're using DRF, which DDT doesn't work well with. DDT is more for template rendered pages, not API responses. Have you brought in Django silk for monitoring this?

https://github.com/jazzband/django-silk/issues?q=is%3Aopen+is%3Aissue+label%3Abug

Are you using Django-silk? Googling for the error shows https://github.com/jazzband/django-silk/issues/374

Those docs are wrong. They still reference syncdb. Use the README at https://github.com/jazzband/django-silk.

Perhaps https://github.com/jazzband/django-silk?

If you're using Django as an API, without templates, django debug toolbar is useless because it requires templates. It won't work with DRF endpoints which means you miss out on profiling and SQL tracing. That's where django-silk shines.

You can also install django-silk to profile your app, and play around with different implementations.

https://github.com/ansible-community/ara/pull/358 https://github.com/b12io/orchestra/pull/830 https://github.com/batiste/django-page-cms/pull/210 https://github.com/carpentries/amy/pull/2130 https://github.com/celery/django-celery/pull/612 https://github.com/django-cms/django-cms/pull/7241 https://github.com/django-oscar/django-oscar/pull/3867 https://github.com/esrg-knights/Squire/pull/253https://github.com/Frojd/django-react-templatetags/pull/64 https://github.com/groveco/django-sql-explorer/pull/474 https://github.com/jazzband/django-silk/pull/550 https://github.com/keras-team/keras/pull/16073 https://github.com/ministryofjustice/cla_backend/pull/773 https://github.com/nitely/Spirit/pull/306 https://github.com/python/pythondotorg/pull/1987 https://github.com/rapidpro/rapidpro/pull/1610 https://github.com/ray-project/ray/pull/22396 https://github.com/saltstack/salt/pull/61647 https://github.com/Swiss-Polar-Institute/project-application/pull/483 https://github.com/UEWBot/dipvis/pull/216

22. Ray | Github | tutorial

Training times for GSM8k are mentioned here: https://github.com/ray-project/ray/tree/master/doc/source/te...

Here's a reference from RLlib that points to docs and an example, and here's one from one of my projects that includes all my own implementations

RLlib

⦿ AWS Glue Data Quality - Automatic data quality rule recommendations based on your data AWS Glue for Ray - Data integration with Ray (ray.io), a popular new open-source compute framework that helps you scale Python workloads

https://ray.io (just dropping the link)

I've wondered whether it's easier to add data analyst stuff to Elixir that Python seems to have, or add features to Python that Erlang (and by extension Elixir) provides out of the box.

By what I can see, if you want multiprocessing on Python in an easier way (let's say running async), you have to use something like ray core[0], then if you want multiple machines you need redis(?). Elixir/Erlang supports this out of the box.

Explorer[1] is an interesting approach, where it uses Rust via Rustler (Elixir library to call Rust code) and uses Polars as its dataframe library. I think Rustler needs to be reworked for this usecase, as it can be slow to return data. I made initial improvements which drastically improves encoding (https://github.com/elixir-nx/explorer/pull/282 and https://github.com/elixir-nx/explorer/pull/286, tldr 20+ seconds down to 3).

[0] https://github.com/ray-project/ray

Adding these for anyone who had a similar question about Ray vs dask 1, 2, 3